Automatic guiding system for analyzing ground texture and method for the same

ABSTRACT

An automatic guiding system for analyzing ground texture in or on an autonomous mobile device comprises an image acquisition module, a ground texture analysis module, a posture sensing module, and a ground texture database. The image acquisition module collects ground images as the autonomous mobile device moves. The ground texture analysis module processes the ground images, and extracts texture information of the ground images. The posture sensing module continuously senses the posture of the autonomous mobile device. The ground texture database is configured to stores the texture information and the posture.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims all benefits accruing under 35 U.S.C. § 119 fromTW Patent Application No. 105102400, filed on Jan. 26, 2016 in the TWIntellectual Property Office, the contents of which are herebyincorporated by reference.

FIELD

The subject matter herein generally relates to an automatic guidingsystem for analyzing ground texture and a method for the same.

BACKGROUND

Simultaneous localization and mapping (SLAM) is commonly used inautonomous mobile devices for positioning. SLAM means the autonomousmobile devices start from an unknown environment location, and establishtheir own location and posture by repeatedly observing map featuresduring a movement; then incrementally constructing a map, so as toachieve a self-locating and map-constructing simultaneously.

However, a displacement or deviation of the autonomous mobile deviceswill be caused by an environment, such as large surface frictioncoefficient, ground potholes, or sand, during movement. The displacementor deviation of the autonomous mobile devices will affect futuredirection and distance of the autonomous mobile devices, and even causethe autonomous mobile devices to be dumped or destroyed.

BRIEF DESCRIPTION OF THE DRAWING

Implementations of the present technology will now be described, by wayof example only, with reference to the attached figures, wherein:

FIG. 1 is a schematic view of a module of an automatic guiding systemfor analyzing ground texture according to one embodiment.

FIG. 2 is a flow chart of an automatic guiding system for analyzingground texture according to one embodiment.

DETAILED DESCRIPTION

The disclosure is illustrated by way of example and not by way oflimitation in the figures of the accompanying drawings in which likereferences indicate similar elements. It should be noted that referencesto “another,” “an,” or “one” embodiment in this disclosure are notnecessarily to the same embodiment, and such references mean “at leastone.”

It will be appreciated that for simplicity and clarity of illustration,where appropriate, reference numerals have been repeated among thedifferent figures to indicate corresponding or analogous elements. Inaddition, numerous specific details are set forth in order to provide athorough understanding of the embodiments described herein. However, itwill be understood by those of ordinary skill in the art that theembodiments described herein can be practiced without these specificdetails. In other instances, methods, procedures, and components havenot been described in detail so as not to obscure the related relevantfeature being described. Also, the description is not to be consideredas limiting the scope of the embodiments described herein. The drawingsare not necessarily to scale and the proportions of certain parts havebeen exaggerated to better illustrate details and features of thepresent disclosure.

Several definitions that apply throughout this disclosure will now bepresented.

The term “substantially” is defined to be essentially conforming to theparticular dimension, shape, or other feature described, such that thecomponent need not be exactly conforming to such feature. The term“comprise,” when utilized, means “include, but not necessarily limitedto”; it specifically indicates open-ended inclusion or membership in theso-described combination, group, series, and the like.

Referring to FIG. 1, the present disclosure is described in relation toan automatic guiding system for analyzing ground texture. The automaticguiding system for analyzing ground texture comprises an imageacquisition module, a ground texture analysis module, a posture sensingmodule, and a ground texture database. The image acquisition module isused to collect ground images in a direction of movement of anautonomous mobile device. The ground texture analysis module isconnected with the image acquisition module. The ground texture analysismodule is used for receiving and processing the ground images andextracting texture information from the ground images. The posturesensing module senses a posture of the autonomous mobile device as theautonomous mobile device moves. The ground texture database is used tostore the texture information and the posture.

The autonomous mobile device can be any mobile device, such as robot orunmanned vehicle.

The image acquisition module comprises a camera. The camera is locatedon a side of the autonomous mobile device facing the direction ofmovement. The camera is used to shoot images of the ground texture. Theground texture can be a surface having a large friction coefficient,such as when there are potholes, sand, gravel, or dirt on the ground.The ground texture can also be relatively smooth, such as a flat ground.The camera can be a web camera based on Charge-coupled Device (CCD) orComplementary Metal Oxide Semiconductor (CMOS).

The ground texture analysis module and the image acquisition module areconnected together. Signals of the ground images acquired by the imageacquisition module are transmitted to the ground texture analysismodule. The ground texture analysis module processes the ground imagebased on a computer vision technology, in order to extract textureinformation. The texture information can be described as featureinformation that can clearly distinguish the ground texture, such as“carpet,” or “ceramic tile.”

The posture sensing module comprises an inertial measurement unit (IMU).The IMU comprises a gyro. An azimuth of the autonomous mobile device canbe obtained by the gyro; changes in the azimuth during movement can beobtained by a mathematical prediction model; and combining the textureinformation extracted by the ground texture analysis module; the postureof the autonomous mobile device can be predicted. The mathematicalprediction model can be Kalman filtering.

The ground texture database stores the texture information of the groundimages and the posture corresponding to the texture information of eachground image. Such as the texture information “carpet” corresponding tothe posture “acceleration to 30 km/h”, and the texture information“ceramic tile” corresponding to the posture “acceleration to 50 km/h”.The ground texture database classified stores the texture information ofthe ground images, and the texture information can be presented in atext form. Developing and refining the texture information continuously,and corrections to the posture corresponding to the texture informationcan be continuously applied, in order to maintain safety of theautonomous mobile device.

The texture information of the ground images corresponds to the postureof the autonomous mobile device. The postures stored in the groundtexture database can not be repeated to prevent confusion.

The automatic guiding system for analyzing ground texture furthercomprises a positioning module, such as a global positioning system(GPS) device. The positioning module is used to obtain a geographicallocation of the autonomous mobile device on a ground. The positioningmodule in combination with the ground texture database inputs thepostures of the autonomous mobile device in different environments atdifferent times into a cloud storage system. Data as to one road sectionunder different environments can be analyzed for obtaining an idealposture of that road section, and the ideal posture is stored in theground texture database. Other autonomous mobile devices can passthrough the road section smoothly and safety just by downloading theground texture database.

The automatic guiding system for analyzing ground texture furthercomprises a data validation module. The data validation module isconnected with the ground texture analysis module and the ground texturedatabase. The data validation module is used to determine if the textureinformation extracted by the ground texture analysis module matches thetexture information stored in the ground texture database. In thiscontext, “matches” means that the texture information extracted by theground texture analysis module is substantially the same as that storedin the ground texture database.

FIG. 2 illustrates one embodiment of a method for the automatic guidingsystem for analyzing ground texture comprising the following steps:

-   -   S1: providing an autonomous mobile device having the automatic        guiding system for analyzing ground texture;    -   S2: collecting the ground images of the autonomous mobile device        in the direction of movement by the image acquisition module,        and transmitting the ground images to the ground texture        analysis module;    -   S3: processing the ground images by the ground texture analysis        module, and extracting first texture information of the ground        images;    -   S4: sensing the posture of the autonomous mobile device by the        posture sensing module, while the autonomous mobile device is on        the ground having the first texture information;    -   S5: comparing the first texture information of the ground images        and second texture information stored in the ground texture        database, judging whether the first texture information of the        ground images already exists in the ground texture database; if        “yes”, finding out the first texture information in the ground        texture database, and suggesting the autonomous mobile device        act accordingly based on the gesture corresponding to the first        texture information in the ground texture database; if “no”,        adding the first texture information of the ground image and        corresponding gesture into the ground texture database; and    -   S6: recording a walking condition of the autonomous mobile        device.

In step S3, a method of processing the ground images by the groundtexture analysis module can comprise the following steps:

-   -   S31: extracting a sub-image constituted by an odd-line pixel;    -   S32: processing the ground images by a median filtering        algorithm to reduce noise in the ground images; and    -   S33: extracting edge points by Canny edge detector.

In step S4, the posture means acceleration, elevation, speed and otherinformation of the autonomous mobile device, while the autonomous mobiledevice is on the ground texture.

In step S6, the autonomous mobile device walks according to the postureof the ground texture database. Reading an output data of the gyro atintervals during walking, and analyzing the output data, such ascreating a chart. If the output data of the gyro is less than a presetthreshold value, a walking condition is “stable”. If the output data ofthe gyro is larger than the preset threshold value, a walking conditionis “unstable”. When the output data of the gyro is larger than thepreset threshold value, feeding the walking condition and the outputdata of the gyro back to the autonomous mobile device, and suggesting arelatively stable posture when the autonomous mobile device walks on thesame ground next time. The “unstable” comprises the autonomous mobiledevice shaking or dumping. The preset threshold value is a data byartificially setting. The data is a threshold of the posture of stablewalking and the posture of unstable walking.

If the autonomous mobile device walks with an instable posture on oneground texture, when the autonomous mobile device walks on that groundtexture next time, the autonomous mobile device will be suggested towalk with the relatively stable posture based on the instable postureand the output data of the gyro. And replacing the instable posture inthe ground texture database with the relatively stable posture togradually optimize the ground texture database.

Depending on the embodiment, certain of the steps of methods describedmay be removed, others may be added, and the sequence of steps may bealtered. It is also to be understood that the description and the claimsdrawn to a method may include some indication in reference to certainsteps. However, the indication used is only to be viewed foridentification purposes and not as a suggestion as to an order for thesteps.

Finally, it is to be understood that the above-described embodiments areintended to illustrate rather than limit the disclosure. Variations maybe made to the embodiments without departing from the spirit of thedisclosure as claimed. Elements associated with any of the aboveembodiments are envisioned to be associated with any other embodiments.The above-described embodiments illustrate the scope of the disclosurebut do not restrict the scope of the disclosure.

What is claimed is:
 1. An automatic guiding system of an autonomousmobile device for analyzing a ground texture comprising: an imageacquisition module configured to collect ground images in a direction ofmovement of the autonomous mobile device; a ground texture analysismodule connected with the image acquisition module, wherein the groundtexture analysis module is configured to receive and process the groundimages, and extract a first texture information of the ground images:wherein the ground texture analysis module is a first processor: aposture sensing module configured to sense a first posture of theautonomous mobile device; a ground texture database that has stored asecond texture information and the first posture; and a data validationmodule connected with the ground texture analysis module, wherein thedata validation module is configured to judge whether the first textureinformation is the same as the second texture information, when thefirst texture information is the same as the second texture information,suggesting the autonomous mobile device to act accordingly based on thefirst posture corresponding to the second texture information; and whenthe first texture information is not the same as the second textureinformation, adding the first texture information and correspondingposture into the ground texture database; wherein the data validationmodule is a second processor.
 2. The system of claim 1, wherein theground texture is selected from the group consisting of potholes, sand,gravel, and dirt.
 3. The system of claim 1, wherein the ground texturecomprises a flat ground.
 4. The system of claim 1, wherein the groundtexture database includes classified second texture information.
 5. Thesystem of claim 4, wherein the texture information is presented in atext form.
 6. The system of claim 1, wherein the image acquisitionmodule comprises a camera located on a side of the autonomous mobiledevice that faces to the direction of movement.
 7. The system of claim1, further comprising a positioning module.
 8. The system of claim 7,wherein the positioning module comprises a global positioning system. 9.A method for an automatic guiding system comprising: step (S1):providing an autonomous mobile device having the automatic guidingsystem; step (S2): collecting ground images of the autonomous mobiledevice in a direction of movement by an image acquisition module, andtransmitting the ground images of the autonomous mobile device in thedirection of movement to a ground texture analysis module; S3:processing the ground images by the ground texture analysis module, andextracting a first texture information of the ground images; S4: sensinga posture of the autonomous mobile device by a posture sensing module;S5: comparing the first texture information of the ground images and asecond texture information stored in a ground texture database, when thefirst texture information of the ground images exists in the groundtexture database, finding out the first texture information in theground texture database, and suggesting the autonomous mobile device toact accordingly based on a first posture corresponding to the firsttexture information in the ground texture database; and when the firsttexture information of the ground images does not exist in the groundtexture database, adding the first texture information of the groundimages and corresponding posture into the ground texture database; andS6: recording a condition of the autonomous mobile device.
 10. Themethod of claim 9, wherein a method of processing the ground images bythe ground texture analysis module comprises: S31: extracting asub-image constituted by an odd-line pixel; S32: processing the groundimages by a median filtering algorithm to reduce noise in the groundimages; and S33: extracting edge points by a Canny edge detector. 11.The method of claim 9, wherein a method of recording the condition ofthe autonomous mobile device comprises: the autonomous mobile devicewalks according to the posture of the ground texture database; readingan output data of a gyro of the posture sensing module at intervalsduring movement, and analyzing the output data; and when the output dataof the gyro is less than a preset threshold value, the condition is“stable”, when the output data of the gyro is larger than the presetthreshold value, the condition is “unstable”.
 12. The method of claim11, wherein when the condition is “unstable”, feeding the condition andthe output data of the gyro back to the autonomous mobile device, andsuggesting a stable posture when the autonomous mobile device walks on asame ground next time; and storing the stable posture in the groundtexture database.
 13. A method for an automatic guiding systemcomprising: step (S1): providing an autonomous mobile device having theautomatic guiding system; step (S2): collecting ground images of theautonomous mobile device in a direction of movement by an imageacquisition module, and transmitting the ground images of the autonomousmobile device in the direction of movement to a ground texture analysismodule; S3: processing the ground images by the ground texture analysismodule, and extracting a first texture information of the ground images;S4: sensing a first posture of the autonomous mobile device by a posturesensing module; S5: comparing the first texture information of theground images and a second texture information stored in a groundtexture database, when the first texture information of the groundimages exists in the ground texture database, finding out the firsttexture information in the ground texture database, and suggesting theautonomous mobile device to act accordingly based on a first posturecorresponding to the first texture information in the ground texturedatabase; and when the first texture information of the ground imagesdoes not exist in the ground texture database, adding the first textureinformation of the ground images and a second posture corresponding tothe first texture information into the ground texture database, whereinthe autonomous mobile device acts based on the second posture; and S6:recording a condition of the autonomous mobile device.